一致性hash(适合py3)

"""
hash_ring
~~~~~~~~~~~~~~
Implements consistent hashing that can be used when
the number of server nodes can increase or decrease (like in memcached).

Consistent hashing is a scheme that provides a hash table functionality
in a way that the adding or removing of one slot
does not significantly change the mapping of keys to slots.

More information about consistent hashing can be read in these articles:

"Web Caching with Consistent Hashing": http://www8.org/w8-papers/2a-webserver/caching/paper2.html 
"Consistent hashing and random trees:
Distributed caching protocols for relieving hot spots on the World Wide Web (1997)": http://citeseerx.ist.psu.edu/legacymapper?did=38148 
Example of usage::

memcache_servers = ['192.168.0.246:11212',
'192.168.0.247:11212',
'192.168.0.249:11212']

ring = HashRing(memcache_servers)
server = ring.get_node('my_key')

:copyright: 2008 by Amir Salihefendic.
:license: BSD
"""

import math
import sys
from bisect import bisect

if sys.version_info >= (2, 5):
import hashlib
md5_constructor = hashlib.md5
else:
import md5
md5_constructor = md5.new

class HashRing(object):

def __init__(self, nodes=None, weights=None):
"""`nodes` is a list of objects that have a proper __str__ representation.
`weights` is dictionary that sets weights to the nodes.  The default
weight is that all nodes are equal.
"""
self.ring = dict()
self._sorted_keys = []

self.nodes = nodes

if not weights:
weights = {}
self.weights = weights

self._generate_circle()

def _generate_circle(self):
"""Generates the circle.
"""
total_weight = 0
for node in self.nodes:
total_weight += self.weights.get(node, 1)

for node in self.nodes:
weight = 1

if node in self.weights:
weight = self.weights.get(node)

factor = math.floor((40*len(self.nodes)*weight) / total_weight)

for j in range(0, int(factor)):
b_key = self._hash_digest( '%s-%s' % (node, j) )

for i in range(0, 3):
key = self._hash_val(b_key, lambda x: x+i*4)
self.ring[key] = node
self._sorted_keys.append(key)

self._sorted_keys.sort()

def get_node(self, string_key):
"""Given a string key a corresponding node in the hash ring is returned.

If the hash ring is empty, `None` is returned.
"""
pos = self.get_node_pos(string_key)
if pos is None:
return None
        return self.ring[ self._sorted_keys[pos] ]

def get_node_pos(self, string_key):
"""Given a string key a corresponding node in the hash ring is returned
along with it's position in the ring.

If the hash ring is empty, (`None`, `None`) is returned.
"""
if not self.ring:
return None
key = self.gen_key(string_key)

nodes = self._sorted_keys
pos = bisect(nodes, key)

if pos == len(nodes):
return 0
else:
return pos

def iterate_nodes(self, string_key, distinct=True):
"""Given a string key it returns the nodes as a generator that can hold the key.

The generator iterates one time through the ring
starting at the correct position.

if `distinct` is set, then the nodes returned will be unique,
i.e. no virtual copies will be returned.
"""
if not self.ring:
yield None, None
returned_values = set()
def distinct_filter(value):
if str(value) not in returned_values:
returned_values.add(str(value))
return value

pos = self.get_node_pos(string_key)
for key in self._sorted_keys[pos:]:
val = distinct_filter(self.ring[key])
if val:
yield val

for i, key in enumerate(self._sorted_keys):
if i < pos:
val = distinct_filter(self.ring[key])
if val:
yield val

def gen_key(self, key):
"""Given a string key it returns a long value,
this long value represents a place on the hash ring.

md5 is currently used because it mixes well.
"""
b_key = self._hash_digest(key)
return self._hash_val(b_key, lambda x: x)

def _hash_val(self, b_key, entry_fn):
return (( b_key[entry_fn(3)] << 24)
|(b_key[entry_fn(2)] << 16)
|(b_key[entry_fn(1)] << 8)
| b_key[entry_fn(0)] )

def _hash_digest(self, key):
m = md5_constructor()
m.update(key.encode('utf-8'))
# return map(ord, m.digest())
return list(m.digest())